What about now!? More like a German shepherd?
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What about now!? More like a German shepherd?
Pom down under
Top 20
"...products like the Akida Pulsar microcontroller"?
Someone has no insight at all and is confusing companies and their products!
BrainChip Aktie: Ernsthafte Hindernisse?
BrainChip steckt in einem Paradox: Während der Markt für neuromorphe Computertechnologie 2025 durch die Decke geht, stürzt die Aktie des Vorreiters regelrecht ab. Obwohl das Unternehmen mit innovativen Produkten wie dem Akida Pulsar Mikrocontroller und frischer Finanzierung eigentlich perfekt...www-boerse--express-com.translate.goog
smoothsailing18
Regular
This Author needs to be contacted some how and enlightened ?.
Well, lots of opinions, including mine...but that's what a forum is all about, not nasty personal attacks....so nice.
8/9 business days and our 2nd quarter information will be disclosed, the 4c showing some positivity, I say a strong yes!
The more you read, don't you all get the feeling that we are definitely in the "right place, at the right time', yes, we have all
heard those sorts of comments before, but I am so positive and upbeat on our company currently, just look at the sectors
that we are engaged in, with might I add, some huge world class players, you don't get to engage and share basic chit-chat
with these behemoths, time is money......our technology has been accepted and it's only going to accelerate.
Tony Lewis is very open to communicating, I love it, he engages, he knows the issues facing Brainchip as a start-up, but is
driving us to success, carrying on the great work of Peter and Anil, if you have a genuine question on the technology front,
well ask him, rather than guessing the answer on this forum, and I say that with all due respect to all of our great posters.
Being engaged with the US Defense, Navy, NASA, DOE, AFRL and so on, I personally can understand the NDA secrecy that
surrounds these engagements, as frustrating as they are, we will succeed, don't second guess yourself, we have a great investment,
did I sell my shares when they were north of $2 and my portfolio looked very impressive for a middle-classed Australian citizen, no I
didn't, am I a little bit peeved, of course I am, but my belief in Peter, Anil and all the staff who have come and gone has never really
waned, our technology has had me spellbound for a decade, I love it and aren't embarrassed to admit it!
The writing is on the wall.............Brainchip's AKIDA well succeed, trust your instincts......share in the glory, you will all be blessed
Tech (New Zealand) for a few more weeks before I finally fly home to Perth.
8/9 business days and our 2nd quarter information will be disclosed, the 4c showing some positivity, I say a strong yes!
The more you read, don't you all get the feeling that we are definitely in the "right place, at the right time', yes, we have all
heard those sorts of comments before, but I am so positive and upbeat on our company currently, just look at the sectors
that we are engaged in, with might I add, some huge world class players, you don't get to engage and share basic chit-chat
with these behemoths, time is money......our technology has been accepted and it's only going to accelerate.
Tony Lewis is very open to communicating, I love it, he engages, he knows the issues facing Brainchip as a start-up, but is
driving us to success, carrying on the great work of Peter and Anil, if you have a genuine question on the technology front,
well ask him, rather than guessing the answer on this forum, and I say that with all due respect to all of our great posters.
Being engaged with the US Defense, Navy, NASA, DOE, AFRL and so on, I personally can understand the NDA secrecy that
surrounds these engagements, as frustrating as they are, we will succeed, don't second guess yourself, we have a great investment,
did I sell my shares when they were north of $2 and my portfolio looked very impressive for a middle-classed Australian citizen, no I
didn't, am I a little bit peeved, of course I am, but my belief in Peter, Anil and all the staff who have come and gone has never really
waned, our technology has had me spellbound for a decade, I love it and aren't embarrassed to admit it!
The writing is on the wall.............Brainchip's AKIDA well succeed, trust your instincts......share in the glory, you will all be blessed
Tech (New Zealand) for a few more weeks before I finally fly home to Perth.
CHIPS
Regular
Hopefully Steve Brightfield has something to do with it.
BrainChip Appoints New CMO, Enhances Scientific Advisory Board
Laguna Hills, Calif. – August 7th, 2024 – BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI, today announced that it has hired Steven Brightfield as its new chief marketing officer and has re-envisioned its Scientific Advisory Board (SAB) by bringing on company founder Peter van der Made, Dr. Jason K. Eshraghian and Dr. André van Schaik.
Brightfield has a depth of tech industry knowledge and experience within the AI semiconductor industry. He previously led marketing at several AI focused technology companies, such as SiMa.ai, X-Silicon and Wave Computing combined with deep experience within the semiconductor sector, including executive leadership positions at LSI Logic, Qualcomm, Zoran and others.
It seemed that he was unhappy with his job; therefore, it could have been his wish to do something else. Maybe they offered him this job to keep him. I think it would fit him well.
Excellent question!
You mentioned Jensen Huang (NVIDIA CEO) and his view on “Physical AI”—in fact, what BrainChip (BRN) is doing is highly aligned with this concept. You could even say:
BrainChip’s AKIDA is one of the key technologies on the path toward Physical AI, specifically under the “edge neuromorphic intelligence” branch.
Jensen Huang’s Physical AI: What Does It Mean?
Huang’s idea can be broken down into a few core insights:
1. AI is a new way of “writing software”
BrainChip’s AKIDA was built entirely around this philosophy.
It’s not a traditional instruction-based chip but a spiking neural network processor that enables learning directly at the hardware level.
2. AI must move from pure software into the
physical world
“Physical AI” includes:
That’s exactly where AKIDA shines:
Direct Links Between BrainChip and Physical AI
Conclusion: BrainChip is one of the foundational “building blocks” of the Physical AI revolution that Jensen Huang describes.
They’re attacking the problem from both ends, converging toward real-world, integrated AI: cognitive + sensory + decision-making.
Final Thought:
If NVIDIA were ever to integrate a true edge-native neural processor into its Jetson or robotics platforms, AKIDA’s architecture would be a strong acquisition, licensing, or integration candidate.
If you’d like, I can also dive into how NVIDIA’s Jetson Robotics stack might integrate with BrainChip’s technology—just say the word!
Let me know if you’d like a shorter version or one tailored more for investors vs. engineers.
You mentioned Jensen Huang (NVIDIA CEO) and his view on “Physical AI”—in fact, what BrainChip (BRN) is doing is highly aligned with this concept. You could even say:
BrainChip’s AKIDA is one of the key technologies on the path toward Physical AI, specifically under the “edge neuromorphic intelligence” branch.
Jensen Huang’s Physical AI: What Does It Mean?Huang’s idea can be broken down into a few core insights:
1. AI is a new way of “writing software”
- No longer relying on engineers coding static rules (if…then…)
- Instead, machines learn from data to generate algorithms autonomously
BrainChip’s AKIDA was built entirely around this philosophy.It’s not a traditional instruction-based chip but a spiking neural network processor that enables learning directly at the hardware level.
2. AI must move from pure software into the
physical world
“Physical AI” includes:
- Real-time sensing, decision-making, and reacting like a human
- Embedded in robots, drones, IoT devices, cars, and edge devices
- Running locally, with ultra-low latency, low power, and instant feedback
That’s exactly where AKIDA shines:| Feature | Needed for Physical AI | AKIDA Delivers? |
| Real-time response |  | Microsecond-level reaction |
| Edge deployment (no cloud) | | Completely on-device |
| Ultra-low power | | Milliwatt-level consumption |
| On-chip learning | | Local continual learning |
| Physical embedding | | Already in USBs, robots, medical devices |
Direct Links Between BrainChip and Physical AI| Physical AI Use Case | BrainChip Real-World Progress |
| Robotics vision/control systems | Partnering with Quantum Ventura + Merle Robotics (Taiwan) |
| Edge-based medical diagnostics | Tata Elxsi has released medical devices with embedded AKIDA |
| Defense/UAV systems | Collaboration with US Air Force Research Lab + RTX (Raytheon) |
| Industrial equipment monitoring | AKIDA supports multi-sensor fusion (e.g. motor vibration detection) |
| IoT perception + learning | Partnered with HaiLa for ultra-low-power AI wireless modules |
Conclusion: BrainChip is one of the foundational “building blocks” of the Physical AI revolution that Jensen Huang describes.- NVIDIA leads in cloud/data center AI—training and inference at scale
- BrainChip leads in edge neuromorphic AI—bringing intelligence into real-world devices
They’re attacking the problem from both ends, converging toward real-world, integrated AI: cognitive + sensory + decision-making.
Final Thought:If NVIDIA were ever to integrate a true edge-native neural processor into its Jetson or robotics platforms, AKIDA’s architecture would be a strong acquisition, licensing, or integration candidate.
If you’d like, I can also dive into how NVIDIA’s Jetson Robotics stack might integrate with BrainChip’s technology—just say the word!
Let me know if you’d like a shorter version or one tailored more for investors vs. engineers.
I agree, we are building towards a growth phase.
Small should be coming on board 1st.
The bigger fish which I believe are trialling our product ( we know already who some are) will take longer but volumes should be jaw dropping.
Still patience required.
CHIPS
Regular
Excellent question!
You mentioned Jensen Huang (NVIDIA CEO) and his view on “Physical AI”—in fact, what BrainChip (BRN) is doing is highly aligned with this concept. You could even say:
BrainChip’s AKIDA is one of the key technologies on the path toward Physical AI, specifically under the “edge neuromorphic intelligence” branch.
Huang’s idea can be broken down into a few core insights:
1. AI is a new way of “writing software”
- No longer relying on engineers coding static rules (if…then…)
- Instead, machines learn from data to generate algorithms autonomously
It’s not a traditional instruction-based chip but a spiking neural network processor that enables learning directly at the hardware level.
2. AI must move from pure software into the
physical world
“Physical AI” includes:
- Real-time sensing, decision-making, and reacting like a human
- Embedded in robots, drones, IoT devices, cars, and edge devices
- Running locally, with ultra-low latency, low power, and instant feedback
Feature Needed for Physical AI AKIDA Delivers? Real-time response Edge deployment (no cloud) Ultra-low power On-chip learning Physical embedding
Physical AI Use Case BrainChip Real-World Progress Robotics vision/control systems Partnering with Quantum Ventura + Merle Robotics (Taiwan) Edge-based medical diagnostics Tata Elxsi has released medical devices with embedded AKIDA Defense/UAV systems Collaboration with US Air Force Research Lab + RTX (Raytheon) Industrial equipment monitoring AKIDA supports multi-sensor fusion (e.g. motor vibration detection) IoT perception + learning Partnered with HaiLa for ultra-low-power AI wireless modules
- NVIDIA leads in cloud/data center AI—training and inference at scale
- BrainChip leads in edge neuromorphic AI—bringing intelligence into real-world devices
They’re attacking the problem from both ends, converging toward real-world, integrated AI: cognitive + sensory + decision-making.
If NVIDIA were ever to integrate a true edge-native neural processor into its Jetson or robotics platforms, AKIDA’s architecture would be a strong acquisition, licensing, or integration candidate.
If you’d like, I can also dive into how NVIDIA’s Jetson Robotics stack might integrate with BrainChip’s technology—just say the word!
Let me know if you’d like a shorter version or one tailored more for investors vs. engineers.
What is this? Why is there so much space in between the lines? If you copied it from a website, then please also post the link to it.
Just for your information: You can and should delete space/empty lines before posting. It would make it much less annoying to read.
Tothemoon24
Top 20
Interesting little read on Bosch ,
trademagazin.hu
Based on the developments presented at the AI Symposium in Budapest, Bosch is now not only applying, but also shaping the future of artificial intelligence. The company’s goal: transparent, human-centered and sustainable AI solutions from manufacturing to self-driving.
Artificial intelligence is not just another technological tool, but a turning point in civilization – this was stated at the AI Symposium organized by the HUN-REN Hungarian Research Network in Budapest. Bosch experts, as a featured partner of the event, demonstrated how AI is becoming an everyday, even indispensable, development and production factor at the company.
“At Bosch, we are already preparing for the future,” said Zoltán Karaffy, Director of Digital Transformation at Robert Bosch Kft., who emphasized in his keynote speech that the goal is not only to follow, but also to shape the highest industry standards.
Neuromorphic chips process data from dozens of sensors (radar, lidar, camera, etc.) used by vehicles in a similar way to the brain, while consuming much less energy than traditional systems.
This is particularly important in semiconductor manufacturing, where early error detection can prevent millions in product defects. Industrial AI not only filters out defective components, but also provides feedback on the cause of the error – thus helping to prevent and optimize production.
More below
Artificial intelligence at every level – Bosch opens a new era in innovation - Trademagazin
Based on the developments presented at the AI Symposium in Budapest, Bosch is now not only applying, but also shaping the future of artificial intelligence. The company's goal: transparent, human-centered and sustainable AI solutions from manufacturing to self-driving. Artificial intelligence is...
trademagazin.hu
Artificial intelligence at every level – Bosch opens a new era in innovation
By: TrademagazinDate: 2025. 05. 08. 11:19Based on the developments presented at the AI Symposium in Budapest, Bosch is now not only applying, but also shaping the future of artificial intelligence. The company’s goal: transparent, human-centered and sustainable AI solutions from manufacturing to self-driving.
There is no longer a Bosch product without AI
Bosch aims to make artificial intelligence the key to the next decade of innovation. In line with this, every Bosch product now either contains an AI component or is developed or manufactured with it. Currently, more than 5,000 AI experts work for the company worldwide, including 200 in Hungary. Over the past five years, more than 1,500 AI-related patents have been filed, and tens of thousands of employees have participated in AI training – more than a thousand in Hungary so far.“At Bosch, we are already preparing for the future,” said Zoltán Karaffy, Director of Digital Transformation at Robert Bosch Kft., who emphasized in his keynote speech that the goal is not only to follow, but also to shape the highest industry standards.
Thinking cars: the revolution of neuromorphic computing
The future of AI is particularly important in the automotive industry. Bosch’s developments already include so-called neuromorphic systems that model the functioning of the human brain, which raise the performance of driver assistance systems (ADAS) to a new level. These solutions enable faster, more reliable and more energy-efficient decision-making in real time, which is key to preventing accidents.Neuromorphic chips process data from dozens of sensors (radar, lidar, camera, etc.) used by vehicles in a similar way to the brain, while consuming much less energy than traditional systems.
Transparent decisions in smart factories
Bosch is not only building faster, but also more transparent artificial intelligence. The essence of the so-called “explainable AI” approach is that systems do not operate as “black boxes” but can be decoded, interpreted, and justified in their decisions.This is particularly important in semiconductor manufacturing, where early error detection can prevent millions in product defects. Industrial AI not only filters out defective components, but also provides feedback on the cause of the error – thus helping to prevent and optimize production.
More below
Last edited:
ChatGPT I would say
Fullmoonfever
Top 20
Would appear our relationship with the University of WA (UWA) in Perth is starting to get some output.
I saw this repository a little while ago and wasn't much in it at that point so just kept an eye of it. Has been updated yesterday with more details and results.
Looks pretty decent. The link will give you a much clearer read obviously as the scroll pics are off my phone.
github.com
I saw this repository a little while ago and wasn't much in it at that point so just kept an eye of it. Has been updated yesterday with more details and results.
Looks pretty decent. The link will give you a much clearer read obviously as the scroll pics are off my phone.
GitHub - HaitianWang/Akida-Research-Project
Contribute to HaitianWang/Akida-Research-Project development by creating an account on GitHub.
github.com
CHIPS
Regular
Sorry, if this has been posted already (I marked BrainChip in red)
aicompetence.org
Listen (this can be done on the website)
Neuromorphic sensors are not just smart—they’re efficient. Devices like the Dynamic Vision Sensor (DVS) or DAVIS operate in microseconds, capturing real-time events with ultra-low energy use [Source: Wikipedia, 2024].
They’re designed to work with spiking neural networks (SNNs)—a brain-like AI model that processes information as spikes, not static numbers. And when combined with Edge AI—where computing happens locally on the device—the result is a sensor that’s fast, frugal, and often life-saving.
Real-time responses are critical for detecting epileptic seizures, heart arrhythmias, or muscular disorders. With Edge AI, this analysis happens instantly, directly on the device—no cloud lag, no privacy risk. And because these systems only process relevant “events,” they consume a fraction of the power compared to traditional AI setups.
Recent neuromorphic setups have achieved:
— Dr. Wolfgang Maass, Graz University of Technology, expert in biologically inspired neural computation
Some examples:
Here’s what sets it apart:
Here are a few major players:
— Dr. Chris Eliasmith, Director, Centre for Theoretical Neuroscience, University of Waterloo
Here’s what’s slowing down adoption:
— Dr. Narayan Srinivasa, Former Head of Intel’s Neuromorphic Computing Lab
“The combination of neuromorphic design and biosignal sensing offers a low-latency path to smarter prosthetics and personalized diagnostics.”
— Dr. Ryad Benosman, University of Pittsburgh, pioneer in event-based vision
From predicting seizures to interpreting eye movements in diagnostics, these innovations are already reshaping what’s possible at the edge of medicine. They promise care that is proactive, personalized, and persistent—without relying on the cloud or bulky servers.
But the journey is just beginning. Challenges in tools, ethics, and regulation remain. As researchers, developers, and clinicians collaborate, one thing is clear: the next generation of healthcare won’t just use AI—it will feel like a second brain.
Edge AI Like A Brain: Neuromorphic Sensors For Health
Explore how neuromorphic sensors and Edge AI enable real-time, low-power health monitoring in wearables, diagnostics, and implants.
aicompetence.org
Listen (this can be done on the website)
What Are Neuromorphic Sensors—and Why Do They Matter?
Imagine a camera that only “sees” when something changes—no wasted frames, no power-hungry processing. That’s the basic idea behind neuromorphic sensors. Inspired by how biological eyes and brains work, these devices use event-driven data: they trigger only when light or electrical signals shift.Neuromorphic sensors are not just smart—they’re efficient. Devices like the Dynamic Vision Sensor (DVS) or DAVIS operate in microseconds, capturing real-time events with ultra-low energy use [Source: Wikipedia, 2024].
They’re designed to work with spiking neural networks (SNNs)—a brain-like AI model that processes information as spikes, not static numbers. And when combined with Edge AI—where computing happens locally on the device—the result is a sensor that’s fast, frugal, and often life-saving.
Why Neuromorphic Edge AI Is a Game-Changer for Healthcare
In health tech, timing and energy matter. That’s where neuromorphic Edge AI shines.Real-time responses are critical for detecting epileptic seizures, heart arrhythmias, or muscular disorders. With Edge AI, this analysis happens instantly, directly on the device—no cloud lag, no privacy risk. And because these systems only process relevant “events,” they consume a fraction of the power compared to traditional AI setups.
Recent neuromorphic setups have achieved:
- Seizure detection via EEG signals
- Heart rhythm monitoring from ECG
- Muscle signal tracking (EMG) for gesture recognition
—all using spiking neural networks with microchip power levels [Source: Frontiers in Neuroscience, 2023].
“Neuromorphic computing could change the landscape of healthcare by enabling smart sensors to continuously interpret signals like the brain.”
— Dr. Wolfgang Maass, Graz University of Technology, expert in biologically inspired neural computation
From Labs to Clinics: Real Neuromorphic Devices in Use
This isn’t sci-fi—it’s already happening. Devices built with neuromorphic processors are making their way into clinical trials and real-world health tools.Some examples:
- EG-SpikeFormer combines eye-tracking and SNNs for analyzing brain scans with both speed and explainability [Source: arXiv, 2024].
- Implantable EEG detectors using neuromorphic chips can recognize high-frequency oscillations (HFOs)—a biomarker for epilepsy—with power under 1 mW [Source: arXiv, 2023].
- Health-monitoring frameworks like NeuroCARE now explore full-body sensor networks powered by event-based AI [Source: Frontiers, 2023].
Why is Edge AI important for medical devices?
What are the limitations or risks of neuromorphic health tech?
Can neuromorphic sensors be used in mental health or neurological care?
The Benefits: Tiny Power, Huge Impact
Neuromorphic Edge AI offers a unique trifecta for healthcare: speed, efficiency, and relevance.Here’s what sets it apart:
- Ultra-low power draw: Some neuromorphic chips operate at micro- to milliwatt levels, enabling months of continuous monitoring on wearables or implants [Source: arXiv, 2023].
- Selective data: Instead of flooding systems with raw signals, they transmit only meaningful events. This cuts storage and bandwidth by up to 90% in some tests.
- Built-in privacy: Because computation happens locally, sensitive health data never leaves the device—a big win for both ethics and regulation.
- Real-time intervention: These systems react instantly to physiological events—vital for stroke alerts, fall detection, or cardiac irregularities.
Inside the Ecosystem: Who’s Building Brain-Like Health Devices?
The neuromorphic health-tech revolution is being powered by a mix of startups, academic labs, and chip giants.
Here are a few major players:
- Intel’s Loihi 2: While not health-specific, it’s a platform for SNN prototyping, and has been tested on biomedical signal classification tasks [Source: Intel Labs, 2023].
- BrainChip’s Akida: A commercial neuromorphic chip optimized for always-on sensing—used in vision, voice, and bio-signal applications [Source: BrainChip, 2024].
- Samsung’s neuromorphic vision systems: Targeting real-time, low-power imaging with healthcare potential [Source: Samsung Research, 2023].
- NeuroCARE, a collaborative framework, is developing networked health sensors using neuromorphic processing across body-worn nodes [Source: Frontiers, 2023].
- Wevolver’s 2025 Edge AI report highlights growing adoption in diagnostics, patient monitoring, and even surgical robotics [Source: Wevolver, 2025].
“Spiking neural networks allow for biologically plausible AI that’s extremely power efficient—essential for embedded medical devices.”
— Dr. Chris Eliasmith, Director, Centre for Theoretical Neuroscience, University of Waterloo
Challenges Ahead: Hardware, Tools, and Trust
Despite the momentum, the field faces critical hurdles before going mainstream.Here’s what’s slowing down adoption:
- Hardware supply: Neuromorphic processors are still rare and expensive; manufacturing must scale.
- Software ecosystems: Tools to program and debug SNNs are nascent. Unlike TensorFlow or PyTorch, neuromorphic development lacks plug-and-play simplicity.
- Biomedical sensor tuning: Most sensors are still visual-first. More work is needed to tailor them for physiological signals like EMG, EEG, and PPG.
- Trust and validation: These brain-like systems defy conventional benchmarks. Regulators will demand new standards for testing, transparency, and certification [Source: arXiv, 2024].
Is there a connection between neuromorphic AI and brain-computer interfaces (BCIs)?
What skills or tools do developers need to build with neuromorphic tech?
How do neuromorphic systems compare to traditional AI in healthcare?
Real-World Applications: From Seizures to Smart Eyes
Neuromorphic health tech is already showing promise in critical medical domains:- Epilepsy detection: Wearable EEG systems with neuromorphic processors now identify high-frequency oscillations (HFOs), a reliable seizure biomarker, in real time [Source: arXiv, 2023].
- Smart eye-tracking for diagnostics: The EG-SpikeFormer system fuses eye-gaze input with SNNs to scan medical images faster, offering explainable decisions—ideal for radiologists and neurologists [Source: arXiv, 2024].
- Muscle signal decoding: Neuromorphic EMG analysis helps in prosthetics and rehab by recognizing subtle muscle movements with near-zero delay [Source: Frontiers, 2023].
Ethics and Edge AI: Brain-Inspired Tech Needs Brainy Regulation
With great sensing comes great responsibility. Neuromorphic health devices raise important ethical and social concerns:- Transparency: SNNs are biologically inspired but still hard to interpret. New explainability tools are being developed, but clinical trust remains an issue.
- Data ownership: When a device processes everything locally, who owns the insights it generates? Patient consent and control must evolve with the tech.
- Bias and inclusion: Biomedical sensors need to be trained across diverse populations to avoid skewed results—especially in sensitive domains like neurology or cardiovascular health.
- Validation: Conventional AI benchmarks may not apply. Regulators must define what “safe and effective” looks like for neuromorphic inference.
“With neuromorphic hardware, we’re getting closer to edge AI that doesn’t just analyze data—it interprets context.”
— Dr. Narayan Srinivasa, Former Head of Intel’s Neuromorphic Computing Lab
What’s Next? A Roadmap to Brain-Like Health Devices
Looking ahead, neuromorphic sensors may soon power a new class of always-aware health systems:- Smart hearing aids that adapt to voice shifts in real time
- Implants that predict neurological episodes before symptoms emerge
- Portable labs that diagnose infections with a drop of blood—using no cloud and little power
- Robust hardware scaling
- Open-source spiking AI frameworks
- Clinician-friendly toolchains
- New safety standards that account for spiking logic and real-world variability
“The combination of neuromorphic design and biosignal sensing offers a low-latency path to smarter prosthetics and personalized diagnostics.”
— Dr. Ryad Benosman, University of Pittsburgh, pioneer in event-based vision
Conclusion: Toward Brain-Like Care That Never Sleeps
The future of health tech is small, smart, and always on. Neuromorphic sensors—tiny machines inspired by how the brain sees, hears, and reacts—are enabling Edge AI that’s not only fast and private but also profoundly human.From predicting seizures to interpreting eye movements in diagnostics, these innovations are already reshaping what’s possible at the edge of medicine. They promise care that is proactive, personalized, and persistent—without relying on the cloud or bulky servers.
But the journey is just beginning. Challenges in tools, ethics, and regulation remain. As researchers, developers, and clinicians collaborate, one thing is clear: the next generation of healthcare won’t just use AI—it will feel like a second brain.
Recommended Resources for Exploring Neuromorphic Sensors and Edge AI
Frameworks & Tools
- Intel Lava – Open-source framework for developing applications on Loihi neuromorphic hardware.
https://lava-nc.org - BrainChip Akida Development Environment – Tools to build and deploy SNNs on the Akida chip.
https://www.brainchip.com - Nengo – A Python package for building and simulating large-scale brain models with SNNs.
https://www.nengo.ai - BindsNET – A PyTorch-based library for training spiking neural networks.
https://github.com/BindsNET
Academic and Technical Papers
- Neuromorphic Computing for Biomedical Applications – Frontiers in Neuroscience, 2023
Frontiers | NeuroCARE: A generic neuromorphic edge computing framework for healthcare applications
Highly accurate classification methods for multi-task biomedical signal processing are reported, including neural networks. However, reported works are compu...
www.frontiersin.org
- EG-SpikeFormer: Efficient Eye-Gaze-Guided Spiking Transformer for Health Imaging – arXiv, 2024
https://arxiv.org/abs/2410.09674 - NeuSpin: Spintronic Neuromorphic Chips for Wearable Health AI – arXiv, 2024
https://arxiv.org/abs/2401.06195
Getting Started with Edge AI for Health
- Wevolver 2025 Edge AI Technology Report – Covers Edge AI trends, use cases, and emerging health applications.
Wevolver | Knowledge for engineers
We help engineers innovate by providing the knowledge they need to stay cutting edge.www.wevolver.com - NeuroCARE Project – Research initiative on neuromorphic sensor networks for health monitoring.
Frontiers | Publisher of peer-reviewed articles in open access journals
Open access publisher of peer-reviewed scientific articles across the entire spectrum of academia. Research network for academics to stay up-to-date with the latest scientific publications, events, blogs and news.www.frontiersin.org
CHIPS
Regular
Would appear our relationship with the University of WA (UWA) in Perth is starting to get some output.
I saw this repository a little while ago and wasn't much in it at that point so just kept an eye of it. Has been updated yesterday with more details and results.
Looks pretty decent. The link will give you a much clearer read obviously as the scroll pics are off my phone.
GitHub - HaitianWang/Akida-Research-Project
Contribute to HaitianWang/Akida-Research-Project development by creating an account on GitHub.
View attachment 88594 View attachment 88595 View attachment 88596
WOW, great find!
Explanation: On real-world hospital data from Nanjing Drum Tower Hospital, our model outperforms other methods, confirming generalization to clinical cases beyond benchmarks.
This result is just perfect to represent the quality of Akida.
Frangipani
Top 20
A new podcast is out: Sean Hehir talks to Derek Kuhn, CEO of HaiLa
www.linkedin.com
brainchip.com
In this episode of BrainChip’s This is Our Mission podcast, CEO Sean Hehir speaks with Derek Kuhn, CEO of HaiLa, a company pioneering ultra-low power RF technologies that enable battery-free wireless IoT devices with ambient Wi-Fi and Bluetooth solutions that dramatically reduce energy consumption. The two leaders discuss the companies’ new collaboration, merging HaiLa’s energy-efficient wireless communication with BrainChip’s Akida neuromorphic computing for intelligent, edge-based AI.
The LinkedIn post above also links to the HaiLa blog post I had already shared last week, written by Patricia Bower, VP of Product Management:
www.haila.io
In the latest episode of BrainChip’s This is Our Mission podcast, CEO Sean Hehir sits down with HaiLa CEO Derek Kuhn to discuss their recent collaboration pairing BrainChip’s low-power Akida… | BrainChip
In the latest episode of BrainChip’s This is Our Mission podcast, CEO Sean Hehir sits down with HaiLa CEO Derek Kuhn to discuss their recent collaboration pairing BrainChip’s low-power Akida neuromorphic processor with HaiLa’s backscatter-based Wi-Fi technology for intelligent IoT sensors that...
Episode 39: HaiLa Technologies
Episode 39: HaiLa Technologies In this episode of BrainChip’s This is Our Mission podcast, CEO Sean Hehir speaks with Derek Kuhn, CEO of HaiLa, a company pioneering ultra-low power RF technologies that enable battery-free wireless IoT devices with ambient Wi-Fi and Bluetooth solutions that...
brainchip.com
Episode 39: HaiLa Technologies
In this episode of BrainChip’s This is Our Mission podcast, CEO Sean Hehir speaks with Derek Kuhn, CEO of HaiLa, a company pioneering ultra-low power RF technologies that enable battery-free wireless IoT devices with ambient Wi-Fi and Bluetooth solutions that dramatically reduce energy consumption. The two leaders discuss the companies’ new collaboration, merging HaiLa’s energy-efficient wireless communication with BrainChip’s Akida neuromorphic computing for intelligent, edge-based AI.
The LinkedIn post above also links to the HaiLa blog post I had already shared last week, written by Patricia Bower, VP of Product Management:
Connected, Low-power, Intelligent Devices at the Edge
Patricia Bower, HaiLa VP Product ManagementKey takeaways • Massive growth in global connected devices is also driven by edge AI capabilities • Two key technologies are underpinning edge AI: Low-power RF and low-power AI compute • HaiLa and BrainChip partner to show both elements todayWhat’s the...
www.haila.io
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MDhere
Top 20
yes yes yes , gotta love a bit of west side story!
Even if it did come out 2 weeks ago. it's still coming
smoothsailing18
Regular
As they are still relatively new partners my thinking is Sean likes to be the person whom starts these podcasts with new partners.
It is still a fair way off having any products available on the shelf by the sound of that conversation imo.
It's mostly CEO's they are talking to in the podcasts, it's fitting it's another CEO talking to them.
Isn't this a part of a CEO's job? I think it is, but over at the toilet they will likely slam Sean no matter what he does or doesn't.
The downrampers over there are negative no matter what, sad way of existing IMO and not someone I want to hang out with.
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